*************************
**** Main Manuscript ****
*************************

*ssc install schemepack /* for figure 4 */
*ssc install estout /* for tables */

*************************
**** Table 1 ****
*************************

* Table 1: Trade Shocks to Industrial Hubs, Peer Networks and Political Responsibility 

use "KimPelc_IO_Dynata.dta", clear

eststo clear

eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

esttab using "Table1.tex", label keep(hub_taa10 nhub_taa10 log_hs_peers union_member) order(hub_taa10 nhub_taa10 log_hs_peers union_member) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*" "Industry Classification FE= *cluster*")

************************************
**** Table 2 & Figure 4 ****
************************************

use "KimPelc_IO_Bilendi.dta", clear

* Table 2: Trade Shock to Industrial Hubs and Individual Perception of Regional Status

eststo clear

eststo: xi: reg ladder_area hub_taa10 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa10 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area nhub_taa10 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area nhub_taa10 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area hub_taa10 nhub_taa10 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa10 nhub_taa10 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

esttab using "Table2.tex", label keep(hub_taa10 nhub_taa10 ladder_self ladder_area_past) order(hub_taa10 nhub_taa10 ladder_self ladder_area_past) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*")

* Figure 4: Coefficient Plots: Trade Shocks and Perception of Regional Status

gen hub_taa = hub_taa5
gen nhub_taa = nhub_taa5

eststo clear
eststo: xi: reg ladder_area hub_taa nhub_taa age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone) 
estimates store m1

eststo: xi: reg ladder_area hub_taa nhub_taa age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone) 
estimates store m2

replace hub_taa = hub_taa10
replace nhub_taa = nhub_taa10

eststo: xi: reg ladder_area hub_taa nhub_taa age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone) 
estimates store m3

eststo: xi: reg ladder_area hub_taa nhub_taa age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone) 
estimates store m4

replace hub_taa = hub_taa15
replace nhub_taa = nhub_taa15

eststo: xi: reg ladder_area hub_taa nhub_taa age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone) 
estimates store m5

eststo: xi: reg ladder_area hub_taa nhub_taa age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone) 
estimates store m6

replace hub_taa = hub_taa20
replace nhub_taa = nhub_taa20

eststo: xi: reg ladder_area hub_taa nhub_taa age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone) 
estimates store m7

eststo: xi: reg ladder_area hub_taa nhub_taa age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone) 
estimates store m8

set scheme white_ptol

label var hub_taa "TAA Demand in Industrial Hubs"
label var nhub_taa "TAA Demand in Non-Hubs"


coefplot (m1, xscale(range(-0.02 0)) label("LQ Top 5%") xline(0) levels(95 90) ciopts(lwidth(medthick thick)) ///
 msymbol(O) pstyle(p1) offset(0.25)) ///
 (m2, label("LQ Top 5%") levels(95 90) ciopts(lwidth(medthick thick)) ///
 msymbol(T) pstyle(p1) offset(0.2)) ///
 (m3, label("LQ Top 10%") levels(95 90) ciopts(lwidth(medthick thick)) ///
 msymbol(O) pstyle(p2) offset(0.1)) ///
 (m4, label("LQ Top 10%") levels(95 90) ciopts(lwidth(medthick thick)) ///
 msymbol(T) pstyle(p2) offset(0.05)) ///
 (m5, label("LQ Top 15%") levels(95 90) ciopts(lwidth(medthick thick)) ///
 msymbol(O) pstyle(p3) offset(-0.05)) ///
 (m6, label("LQ Top 15%") levels(95 90) ciopts(lwidth(medthick thick)) ///
 msymbol(T) pstyle(p3) offset(-0.1)) ///
 (m7, label("LQ Top 20%") levels(95 90) ciopts(lwidth(medthick thick)) ///
 msymbol(O) pstyle(p4) offset(-0.2)) ///
 (m8, label("LQ Top 20%") levels(95 90) ciopts(lwidth(medthick thick)) ///
 msymbol(T) pstyle(p4) offset(-0.25)), ///
	byopts(compact cols(4)) keep(hub_taa nhub_taa) xlabel(,labsize(med)) ylabel(,labsize(med)) ///
 legend(order(3 "LQ Top 5%" 9 "LQ Top 10%" 15 "LQ Top 15%" 21 "LQ Top 20%" ///
	 ///
 99 "." ///
 ///
 3 "Base Model" 6 "Base Model" "+ Additional Control") ///
 region(style(none)) cols(1) )

graph save "Figure4.gph", replace
graph export "Figure4.pdf", replace
		 
*****************
**** Table 3 ****
*****************
		 
* Table 3: Perception of Regional Standing and Populist Attitude

use "KimPelc_IO_Respondi.dta", clear

eststo clear

eststo: xi: reg thickpopulism ladder_avpersarea age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division, cluster(czone)
eststo: xi: reg thickpopulism ladder_personal age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division, cluster(czone)
eststo: xi: reg thickpopulism ladder_avpersarea ladder_personal age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division, cluster(czone)

eststo: xi: reg thickpopulism ladder_avpersarea age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division if high_shock == 0, cluster(czone)
eststo: xi: reg thickpopulism ladder_personal age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division if high_shock == 0, cluster(czone)

eststo: xi: reg thickpopulism ladder_avpersarea age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division if high_shock == 1, cluster(czone)
eststo: xi: reg thickpopulism ladder_personal age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division if high_shock == 1 , cluster(czone)

esttab using "Table3.tex", label keep(ladder_avpersarea ladder_personal) ///
	order(ladder_avpersarea ladder_personal) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*")

*****************
**** Table 4 ****
*****************

* Table 4: Trade Shock to Industrial Hubs and Support for the Republican Party	

use "KimPelc_IO_Election.dta", clear

eststo clear 

eststo: reg depvar hub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar hub_taa10 nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa10 nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

esttab using "Table4.tex", label keep(hub_taa10 nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource) order(hub_taa10 nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *reg_midatl*" "2000 demographic controls = *l_sh_pop_f*" "1996/2000 presidential election controls=shnr_pres1996")

********************************
**** Supplementary Appendix ****
********************************

**************************************
****      Tables A3, A12-A15      ****
**************************************

use "KimPelc_IO_Dynata.dta", clear

* Table A3: Summary Statistics: Respondents Recruited by Dynata

eststo clear
estpost summarize lq_cz_cluster hub_region hub_taa10 nhub_taa10 age male race_others black hispanic asian college union_member income_relative gop dem pols_responsible 
esttab using "TableA3.tex", cells("count mean(fmt(2)) sd(fmt(2)) min(fmt(2)) max(fmt(2))") nomtitle label replace b(3)

* Table A11: Industrial Hubs and Peer Networks

eststo clear

eststo: xi: reghdfe log_hs_peers lq_cz_cluster age male race_others black hispanic asian college gop dem, noabsorb cluster(czone) 
eststo: xi: reghdfe log_hs_peers hub_region age male race_others black hispanic asian college gop dem, noabsorb cluster(czone) 
esttab using "TableA11.tex", label keep(lq_cz_cluster hub_region age male race_others black hispanic asian college gop dem) ///
 order(lq_cz_cluster hub_region age male race_others black hispanic asian college gop dem) addnotes("Standard errors clustered by commuting zones in parentheses." "\textit{+p < 0.10, * p < 0.05, ** p < 0.01}" ) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars 


* Table A12: Trade Shocks to Industrial Hubs, Peer Networks and Political Responsibility: Full Results
 
eststo clear

eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

esttab using "TableA12.tex", label keep(log_hs_peers hub_taa10 nhub_taa10 union_member age male race_others black hispanic asian college income_relative gop dem) order(hub_taa10 nhub_taa10 log_hs_peers union_member age male race_others black hispanic asian college union_member income_relative gop dem) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*" "Industry Classification FE= *cluster*")


* Table A13: Trade Shocks to Industrial Hubs, Peer Networks and Political Responsibility: 95th percentile

eststo clear

eststo: xi: reg pols_responsible hub_taa5 nhub_taa5 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa5 nhub_taa5 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible hub_taa5 nhub_taa5 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa5 nhub_taa5 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

esttab using "TableA13.tex", label keep(hub_taa5 nhub_taa5 log_hs_peers union_member age male race_others black hispanic asian college gop dem) order(hub_taa5 nhub_taa5 log_hs_peers union_member age male race_others black hispanic asian college income_relative gop dem) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*" "Industry Classification FE= *cluster*")

* Table A14: Trade Shocks to Industrial Hubs, Peer Networks and Political Responsibility: 85th percentile

eststo clear

eststo: xi: reg pols_responsible hub_taa15 nhub_taa15 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa15 nhub_taa15 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible hub_taa15 nhub_taa15 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa15 nhub_taa15 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)


esttab using "TableA14.tex", label keep(hub_taa15 nhub_taa15 log_hs_peers union_member age male race_others black hispanic asian college income_relative gop dem) order(hub_taa15 nhub_taa15 log_hs_peers union_member age male race_others black hispanic asian college income_relative gop dem) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*" "Industry Classification FE= *cluster*")

* Table A15: Trade Shocks to Industrial Hubs, Peer Networks and Political Responsibility: 80th percentile

eststo clear

eststo: xi: reg pols_responsible hub_taa20 nhub_taa20 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa20 nhub_taa20 age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible hub_taa20 nhub_taa20 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa20 nhub_taa20 log_hs_peers age male race_others black hispanic asian college union_member income_relative gop dem i.census_division i.cluster_code, cluster(czone)

esttab using "TableA15.tex", label keep(hub_taa20 nhub_taa20 log_hs_peers union_member age male race_others black hispanic asian college income_relative gop dem) order(hub_taa20 nhub_taa20 log_hs_peers union_member age male race_others black hispanic asian college income_relative gop dem) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*" "Industry Classification FE= *cluster*")

* Table A16: Trade Shocks to Industrial Hubs, Peer Networks and Political Responsibility: Full Results with Limited Controls

eststo clear

eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 age male race_others black hispanic asian college i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 age male race_others black hispanic asian college i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college i.census_division, cluster(czone)
eststo: xi: reg pols_responsible log_hs_peers age male race_others black hispanic asian college i.census_division i.cluster_code, cluster(czone)

eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 log_hs_peers age male race_others black hispanic asian college i.census_division, cluster(czone)
eststo: xi: reg pols_responsible hub_taa10 nhub_taa10 log_hs_peers age male race_others black hispanic asian college i.census_division i.cluster_code, cluster(czone)

esttab using "TableA16.tex", label keep(log_hs_peers hub_taa10 nhub_taa10 age male race_others black hispanic asian college) order(hub_taa10 nhub_taa10 log_hs_peers age male race_others black hispanic asian college) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*" "Industry Classification FE= *cluster*")
 
**************************************
****      Tables A4, A16-A20      ****
**************************************

use "KimPelc_IO_Bilendi.dta", clear

* Table A4: Summary Statistics: Respondents Recruited by Bilendi

eststo clear
estpost summarize hub_taa10 nhub_taa10 age male race_others black hispanic asian college gop dem income ladder_area ladder_self ladder_area_past 
esttab using "TableA4.tex", cells("count mean(fmt(2)) sd(fmt(2)) min(fmt(2)) max(fmt(2))") nomtitle label replace b(3)


* Table A17: Trade Shock to Industrial Hubs and Individual Perception of Regional Standing: Full Results

eststo clear

eststo: xi: reg ladder_area hub_taa10 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa10 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area nhub_taa10 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area nhub_taa10 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area hub_taa10 nhub_taa10 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa10 nhub_taa10 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

esttab using "TableA17.tex", label keep(hub_taa10 nhub_taa10 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college gop dem income) order(hub_taa10 nhub_taa10 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college gop dem income) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*")

* Table A18: Trade Shock to Industrial Hubs and Individual Perception of Regional Standing: 95th Percentile

eststo clear

eststo: xi: reg ladder_area hub_taa5 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa5 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area nhub_taa5 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area nhub_taa5 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area hub_taa5 nhub_taa5 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa5 nhub_taa5 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

esttab using "TableA18.tex", label keep(hub_taa5 nhub_taa5 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college gop dem income) order(hub_taa5 nhub_taa5 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college gop dem income) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*")

* Table A19: Trade Shock to Industrial Hubs and Individual Perception of Regional Standing: 85th Percentile

eststo clear

eststo: xi: reg ladder_area hub_taa15 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa15 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area nhub_taa15 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area nhub_taa15 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area hub_taa15 nhub_taa15 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa15 nhub_taa15 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

esttab using "TableA19.tex", label keep(hub_taa15 nhub_taa15 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college gop dem income) order(hub_taa15 nhub_taa15 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college gop dem income) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*")

* Table A20: Trade Shock to Industrial Hubs and Individual Perception of Regional Standing: 80th Percentile

eststo clear

eststo: xi: reg ladder_area hub_taa20 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa20 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area nhub_taa20 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area nhub_taa20 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area hub_taa20 nhub_taa20 age male race_others black hispanic asian college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa20 nhub_taa20 age male race_others black hispanic asian college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

esttab using "TableA20.tex", label keep(hub_taa20 nhub_taa20 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college gop dem income) order(hub_taa20 nhub_taa20 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college gop dem income) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*")

* Table A21: Trade Shock to Industrial Hubs and Individual Perception of Regional Standing: Full Results with Limited Controls

eststo clear

eststo: xi: reg ladder_area hub_taa10 age male race_others black hispanic asian college ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa10 age male race_others black hispanic asian college ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area nhub_taa10 age male race_others black hispanic asian college ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area nhub_taa10 age male race_others black hispanic asian college ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area hub_taa10 nhub_taa10 age male race_others black hispanic asian college ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa10 nhub_taa10 age male race_others black hispanic asian college ladder_self ladder_area_past i.census_division, cluster(czone)

esttab using "TableA21.tex", label keep(hub_taa10 nhub_taa10 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college) order(hub_taa10 nhub_taa10 ladder_self ladder_area_past ladder_self ladder_area_past age male black hispanic asian race_others college) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*")

* Table A22: Trade Shock to Industrial Hubs and Individual Perception of Regional Standing: Interaction with Race

eststo clear

eststo: xi: reg ladder_area hub_taa10 non_white hub_shock_nonwhite age male college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa10 non_white hub_shock_nonwhite age male college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone) 

eststo: xi: reg ladder_area nhub_taa10 non_white nhub_shock_nonwhite age male college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area nhub_taa10 non_white nhub_shock_nonwhite age male college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

eststo: xi: reg ladder_area hub_taa10 non_white hub_shock_nonwhite nhub_taa10 nhub_shock_nonwhite age male college gop dem income ladder_self i.census_division, cluster(czone)
eststo: xi: reg ladder_area hub_taa10 non_white hub_shock_nonwhite nhub_taa10 nhub_shock_nonwhite age male college gop dem income ladder_self ladder_area_past i.census_division, cluster(czone)

esttab using "TableA22.tex", label keep(hub_taa10 nhub_taa10 hub_shock_nonwhite nhub_shock_nonwhite non_white age male college gop dem income ladder_self ladder_area_past) order(hub_taa10 nhub_taa10 hub_shock_nonwhite nhub_shock_nonwhite non_white age male college gop dem income ladder_self ladder_area_past) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*")

**************************************
****       Tables A5 & A20B       ****
**************************************

use "KimPelc_IO_Respondi.dta", clear

* Table A5: Summary Statistics: Respondents Recruited by Respondi

eststo clear
estpost summarize thickpopulism ladder_avpersarea ladder_personal age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease
esttab using "TableA5.tex", cells("count mean(fmt(2)) sd(fmt(2)) min(fmt(2)) max(fmt(2))") nomtitle label replace b(3)

* Table A23: Perception of Regional Standing and Populist Attitude: Full Results

eststo clear

eststo: xi: reg thickpopulism ladder_avpersarea age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division, cluster(czone)
eststo: xi: reg thickpopulism ladder_personal age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division, cluster(czone)
eststo: xi: reg thickpopulism ladder_avpersarea ladder_personal age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division, cluster(czone)

eststo: xi: reg thickpopulism ladder_avpersarea age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division if high_shock == 0, cluster(czone)
eststo: xi: reg thickpopulism ladder_personal age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division if high_shock == 0, cluster(czone)

eststo: xi: reg thickpopulism ladder_avpersarea age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division if high_shock == 1, cluster(czone)
eststo: xi: reg thickpopulism ladder_personal age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease i.census_division if high_shock == 1 , cluster(czone)

esttab using "TableA23.tex", label keep(ladder_avpersarea ladder_personal age age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease) ///
	order(ladder_avpersarea ladder_personal age age male college_grad race_others black hispanic asian under50k incomechange_last3_decrease) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *census*")

****************************************
****    Table A7, A8 and A21-A26    ****
****************************************

use "KimPelc_IO_Election.dta", clear

* Table A7: Summary Statistics: County-Level and CZ-Level Data

eststo clear
estpost summarize depvar hub_taa10 nhub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic 
esttab using "TableA7.tex", cells("count mean(fmt(2)) sd(fmt(2)) min(fmt(2)) max(fmt(2))") nomtitle label replace b(3)

* Table A8: Correlation Table

eststo clear
estpost correlate depvar hub_taa10 nhub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic , matrix listwise 
esttab using "TableA8.tex", replace unstack not noobs compress cells(rho(fmt(2))) label 

* Table A24: Trade Shock to Industrial Hubs and Support for the Republican Party: Full results

eststo clear 

eststo: reg depvar hub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar hub_taa10 nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa10 nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

esttab using "TableA24.tex", label keep(hub_taa10 nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic ) order(hub_taa10 nhub_taa10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *reg_midatl*")

* Table A25: Trade Shock to Industrial Hubs and Support for the Republican Party: 95th Percentile

eststo clear 

eststo: reg depvar hub_taa5 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa5 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar nhub_taa5 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar nhub_taa5 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar hub_taa5 nhub_taa5 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa5 nhub_taa5 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

esttab using "TableA25.tex", label keep(hub_taa5 nhub_taa5 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic ) order(hub_taa5 nhub_taa5 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *reg_midatl*")

* Table A26: Trade Shock to Industrial Hubs and Support for the Republican Party: 85th Percentile

eststo clear 

eststo: reg depvar hub_taa15 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa15 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar nhub_taa15 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar nhub_taa15 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar hub_taa15 nhub_taa15 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa15 nhub_taa15 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

esttab using "TableA26.tex", label keep(hub_taa15 nhub_taa15 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic ) order(hub_taa15 nhub_taa15 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *reg_midatl*")

* Table A27: Trade Shock to Industrial Hubs and Support for the Republican Party: 80th Percentile	
	
eststo clear 

eststo: reg depvar hub_taa20 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa20 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar nhub_taa20 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar nhub_taa20 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar hub_taa20 nhub_taa20 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa20 nhub_taa20 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

esttab using "TableA27.tex", label keep(hub_taa20 nhub_taa20 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic ) order(hub_taa20 nhub_taa20 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *reg_midatl*")

* Table A28: Trade Shock to Industrial Hubs and Support for the Republican Party: Controlling for Chinese Imports Shock

eststo clear 

eststo: reg depvar hub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000  reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar nhub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar nhub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar hub_taa10 nhub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_taa10 nhub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

esttab using "TableA28.tex", label keep(hub_taa10 nhub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic ) order(hub_taa10 nhub_taa10 d_imp_usch_pd_0008 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000 l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars indicate("Census Division FE = *reg_midatl*")

* Table A29: Labor Market Changes in Industrial Clusters and Support for the Republican Party: Within Manufacturing

eststo clear 

eststo: reg depvar hub_manf_taa_10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_manf_taa_10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000  reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar hub_n_manf_taa_10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_n_manf_taa_10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000  reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

eststo: reg depvar hub_manf_taa_10 hub_n_manf_taa_10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)
eststo: reg depvar hub_manf_taa_10 hub_n_manf_taa_10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000  reg_midatl reg_encen reg_wncen reg_satl reg_escen reg_wscen reg_mount reg_pacif l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic [aw=weight], cluster(czone)

esttab using "TableA29.tex", label keep(hub_manf_taa_10 hub_n_manf_taa_10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000  l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic ) order(hub_manf_taa_10 hub_n_manf_taa_10 l_shind_manuf_cbp l_sh_routine33 l_task_outsource shnr_pres1996 shnr_pres2000  l_sh_pop_f l_sh_pop_edu_c l_sh_fborn l_sh_pop_age_1019 l_sh_pop_age_2029 l_sh_pop_age_3039 l_sh_pop_age_4049 l_sh_pop_age_5059 l_sh_pop_age_6069 l_sh_pop_age_7079 l_sh_pop_age_8000 l_sh_pop_white l_sh_pop_black l_sh_pop_asian l_sh_pop_hispanic)  nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars  indicate("Census Division FE = *reg_midatl*")

****************************************
****            Table A9            ****
****************************************

use "KimPelc_IO_CZ_Cluster.dta", clear

* Table A9: Industrial Hubs and Trade-Related Shocks

eststo clear 
eststo: xi: reghdfe log_hub_taa_w_pw hub, noabsorb cluster(czone cluster_code)
eststo: xi: reghdfe log_hub_taa_w_pw hub, absorb(czone) cluster(czone cluster_code)
eststo: xi: reghdfe log_hub_taa_w_pw hub i.cluster_code, absorb(czone) cluster(czone cluster_code)
esttab using "TableA9.tex", label keep(hub) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars 

********************************************
****          Table A10                 ****
********************************************

use "KimPelc_IO_CZ.dta", clear

* Table A10: Hub and Chinese Imports Shock 

eststo clear 
eststo: reg  d_imp_usch_pd_0008 hub_cz

esttab using "TableA10.tex", label keep(hub_cz) order(hub_cz) nonotes se(3) b(3) replace star(+ 0.10 * 0.05 ** 0.01) compress nogaps nodepvars 
